bradyz/2020_CARLA_challenge
"Learning by Cheating" (CoRL 2019) submission for the 2020 CARLA Challenge
This project helps autonomous driving researchers train and evaluate self-driving car agents in simulated urban environments. It takes in car sensor data (RGB images, semantic segmentation) and vehicle position/heading, then outputs control commands like steer, throttle, and brake. Researchers and engineers working on perception and control systems for autonomous vehicles would use this.
188 stars. No commits in the last 6 months.
Use this if you are developing or evaluating self-driving car algorithms and need a robust simulation environment and data for training agents to navigate complex urban routes.
Not ideal if you are looking for a plug-and-play solution for real-world autonomous driving or a tool for general-purpose robot navigation outside of the CARLA simulator.
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Nov 13, 2020
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